Automatic Identification System (AIS) data holds significant potential for capturing and analysing activities at sea. For offshore wind developers and operators seeking lower emissions using uncrewed surface vessels (USVs) and other alternatives to conventionally crewed vessels, analysis of AIS enables understanding of how such craft ...
Automatic Identification System (AIS) data holds significant potential for capturing and analysing activities at sea. For offshore wind developers and operators seeking lower emissions using uncrewed surface vessels (USVs) and other alternatives to conventionally crewed vessels, analysis of AIS enables understanding of how such craft can be incorporated into different operations. This research presents a methodology, using archived AIS data to trace the movements of vessels and identify relevant activities. Our findings demonstrate how archived AIS data combined with both public sources of contextual information and expert knowledge regarding the activities, can enable the characterization of previous site investigation surveys and the inspection of subsea structures, and so identify specific applications of USVs in these scenarios throughout the development and operation of offshore wind projects.
